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Spotify
Senior Machine Learning Engineer, Enrichment & Content Intelligence
Spotify
New York•On-site•Salary•4-7 Yrs•2 hours ago
Job description
MLMultimodalContent IntelligenceSpotify
Overview
Senior Machine Learning Engineer for Spotify's Enrichment & Content Intelligence team. Build the metadata-resolution and content-enrichment infrastructure that powers how Spotify understands music and video content at global scale.
Responsibilities
- Own and evolve large-scale ML pipelines powering Spotify’s content-resolution systems
- Lead development of multimodal embedding frameworks supporting multimodal understanding, music video matching, SongDNA
- Improve entity-resolution systems across music and video content
- Design and run experiments to improve precision, recall, and overall content-quality outcomes using offline evaluation, golden datasets, A/B testing, and impact analysis
- Build scalable ML evaluation and monitoring infrastructure
- Contribute to the evolution of the Music Knowledge Graph by improving production ML capabilities, observability, and model lifecycle management
- Partner closely with Product Managers, Data Scientists, and engineering teams across Content Platform and the wider Experience Mission
- Help shape technical strategy for the squad and contribute to long-term ML direction across the product area
- Mentor engineers and contribute to a strong culture of technical collaboration and experimentation
Qualifications
- Solid experience building, deploying, and maintaining machine learning systems in production at scale
- Strong experience training, evaluating, and operating ML models using modern frameworks such as PyTorch or TensorFlow
- Experience working with multimodal machine learning systems across audio, computer vision, text embeddings, or related domains
- Understand entity resolution, deduplication, record linkage, or large-scale matching problems, ideally across multiple content modalities
- Know how to design evaluation systems that balance model quality, operational performance, and real-world impact
- Experienced working with large-scale distributed data processing systems and ML infrastructure
- Communicate effectively across engineering, product, and data science stakeholders
- Comfortable leading technical initiatives and influencing engineering direction within a team
Nice to have
- Experience with Scio, Dataflow, Flyte, BigQuery, or similar distributed processing frameworks
- Experience with Scala
- Computer vision, video understanding, multimodal embeddings, or recommendation systems
Benefits
- Health insurance
- Six-month paid parental leave
- 401(k) retirement plan
- Monthly meal allowance
- 23 paid days off
- Paid flexible holidays
- Paid sick leave
- Extensive learning opportunities through GreenHouse
- Flexible share incentives
- Global parental leave, six months off - for all new parents
- All The Feels, our employee assistance program and self-care hub
- Flexible public holidays, swap days off